Author

Jing Liu

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Open access Aug 2026

Tensor-Network Markov-Chain Monte Carlo: Efficient Sampling of Three-Dimensional Spin Glasses.

Sampling equilibrium configurations of three-dimensional (3D) spin glasses with quenched disorder remains a fundamental challenge in statistical physics. The rugged energy landscape, pronounced critical slowing down, and intrinsic ergodicity breaking render standard Monte Carlo methods severely inefficient, particularl...

Tao Chen, Jing Liu, You-Jin Deng et al. · Physical Review Letters · 1 citation

Preprint Aug 2026

Exact autoregressive sampling of planar Ising spin glasses via the Kac--Ward theory

Exact sampling from the Boltzmann distribution of spin glasses remains an outstanding challenge: Markov chain Monte Carlo methods suffer from critical slowing down and metastable trapping, while modern neural autoregressive samplers such as variational autoregressive networks are approximate and, in the absence of exac...

Jing Liu, Tao Chen, Tianrui Che et al. · 0 citations